📂Tomography

How to Use the Shepp-Logan Phantom in Julia, MATLAB, and Python

Julia¹

To use the Tomography package Tomography.jl, you can use the phantom() function.

• phantom(m,n=1): Generates a Shepp-Logan phantom of size $m\times m$. When n=1, it generates a Shepp-Logan phantom, and when n=2, it generates a Modified Shepp-Logan phantom.

using Tomography
using Plots

# 팬텀 생성
p = phantom(256,2)

# 그림 출력
heatmap(reverse(p, dims=1))

Environment

• OS: Windows10
• Version: Julia 1.7.1, Tomography 0.1.5

MATLAB²

You can create a Shepp-Logan phantom with phantom. Without any arguments, an array of size $256 \times 256$ is created. The first argument specifies the type of phantom, and the second argument specifies the size to generate an arbitrary phantom. Below are the example code and the result.

%팬텀 생성
p1 = phantom();
p2 = phantom('Modified Shepp-Logan',2^10);

%그림 출력
figure()

%첫번째 그림 p1
subplot(1,2,1)
imagesc(p1)
colorbar
title('p1')

%두번째 그림 p2
subplot(1,2,2)
imagesc(p2)
colorbar
title('p2')

Environment

• OS: Windows10
• Version: R2020b

Python³

In the scikit-image package skimage’s data module, you can use the shepp_logan_phantom function. It generates a phantom of size $400 \times 400$. To change the size, you can use resize. Below are the example code and the result.

import matplotlib.pyplot as plt

from skimage.data import shepp_logan_phantom

# 팬텀 생성
P = shepp_logan_phantom() #default size=(400,400)

# 그림 출력
plt.imshow(P)
plt.show()

# 사이즈 변경
from skimage.transform import resize

P = shepp_logan_phantom()
P = resize(P, (256,256))

Environment

• OS: Windows10
• Version: Python 3.9.2, scikit-image 0.18.1